---
license: apache-2.0
base_model: allenai/OLMo-3-7B-RLZero-Math
language:
- en
library_name: transformers
tags:
- gguf
- mlx
- ollama
- math
- reasoning
- olmo
- quantized
pipeline_tag: text-generation
---

# OLMo-3-7B-RLZero-Math GGUF

> **GGUF & MLX quantizations** of Allen Institute for AI's mathematical reasoning model, optimized for local inference with llama.cpp, Ollama, and Apple Silicon.

## Highlights

| | |
|---|---|
| **Math Specialist** | Fine-tuned with RL-Zero for step-by-step mathematical reasoning |
| **65K Context** | 65,536 token context window with YaRN scaling |
| **Apple Silicon Ready** | MLX-optimized 4-bit quantization included |
| **Runs Anywhere** | From 4GB RAM to full precision |

## Model Specifications

| Property | Value |
|----------|-------|
| **Parameters** | 7 billion |
| **Architecture** | OLMo2 |
| **Context Length** | 65,536 tokens |
| **Training** | RL-Zero mathematical reasoning |
| **License** | Apache 2.0 |

## Available Versions

### GGUF Quantizations

| Quantization | Size | Quality | Use Case |
|--------------|------|---------|----------|
| `F16` | 14 GB | Near-perfect | Maximum quality, research |
| `Q8_0` | 7.2 GB | Excellent | Near-lossless, high-end hardware |
| `Q5_K_M` | 4.9 GB | Very Good | Excellent quality/size balance |
| `Q4_K_M` | 4.2 GB | Good | **Recommended** for most users |
| `IQ4_XS` | 3.8 GB | Good | Compact 4-bit |
| `IQ3_M` | 3.2 GB | Acceptable | Ultra-compact, constrained devices |

### MLX (Apple Silicon)

4-bit quantized version in `MLX-4bit/` folder - optimized for M1/M2/M3/M4 Macs.

## Quick Start

### Ollama (Easiest)

```bash
ollama run richardyoung/olmo-3-7b-rlzero-math
```

### llama.cpp

```bash
# Download Q4_K_M (recommended)
wget https://huggingface.co/richardyoung/OLMo-3-7B-RLZero-Math-GGUF/resolve/main/Olmo-3-7B-RLZero-Math-Q4_K_M.gguf

# Run inference
./llama-cli -m Olmo-3-7B-RLZero-Math-Q4_K_M.gguf \
  -p "Solve step by step: What is 15% of 240?" \
  -n 512
```

### MLX (Apple Silicon)

```bash
pip install mlx-lm

mlx_lm.generate \
  --model richardyoung/OLMo-3-7B-RLZero-Math-GGUF \
  --prompt "Solve: Find the derivative of x^3 + 2x" \
  --trust-remote-code
```

### Python

```python
from llama_cpp import Llama

llm = Llama(
    model_path="Olmo-3-7B-RLZero-Math-Q4_K_M.gguf",
    n_ctx=4096
)

output = llm(
    "Solve step by step: What is the sum of the first 10 prime numbers?",
    max_tokens=512
)
print(output["choices"][0]["text"])
```

## System Requirements

| Quantization | Min RAM | Recommended | Apple Silicon |
|--------------|---------|-------------|---------------|
| IQ3_M | 4 GB | 8 GB | M1 8GB |
| IQ4_XS / Q4_K_M | 6 GB | 12 GB | M1 8GB |
| Q5_K_M / Q8_0 | 8 GB | 16 GB | M1 16GB |
| F16 | 16 GB | 24 GB | M2 Pro+ |

## Prompt Format

```
Solve the following math problem step by step:
{your problem here}
```

**Example:**
```
Solve the following math problem step by step:
A train travels 120 miles in 2 hours. If it continues at the same speed,
how long will it take to travel 300 miles?
```

## Links

| Resource | Link |
|----------|------|
| **Original Model** | [allenai/OLMo-3-7B-RLZero-Math](https://huggingface.co/allenai/OLMo-3-7B-RLZero-Math) |
| **Ollama** | [richardyoung/olmo-3-7b-rlzero-math](https://ollama.com/richardyoung/olmo-3-7b-rlzero-math) |
| **Allen AI** | [allenai.org](https://allenai.org/) |

---

**Quantization by** [Richard Young](https://huggingface.co/richardyoung) | **Original model by** [Allen Institute for AI](https://allenai.org/)